Robust Safety-Critical Control for Dynamic Robotics

We present a novel method of optimal robust control through quadratic programs that offers tracking stability while subject to input and state-based constraints as well as safety-critical constraints for nonlinear dynamical robotic systems in the presence of model uncertainty. The proposed method fo...

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Bibliographic Details
Published inIEEE transactions on automatic control Vol. 67; no. 3; pp. 1073 - 1088
Main Authors Nguyen, Quan, Sreenath, Koushil
Format Journal Article
LanguageEnglish
Published New York IEEE 01.03.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Contact force
Control stability
Control systems
Legged locomotion
Lyapunov methods
Optimal control
Perturbation
quadratic programming
robot control
Robotics
Robots
Robust control
Safety critical
Stability analysis
Uncertainty
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Summary:We present a novel method of optimal robust control through quadratic programs that offers tracking stability while subject to input and state-based constraints as well as safety-critical constraints for nonlinear dynamical robotic systems in the presence of model uncertainty. The proposed method formulates robust control Lyapunov and barrier functions to provide guarantees of stability and safety in the presence of model uncertainty. We evaluate our proposed control design on dynamic walking of a five-link planar bipedal robot subject to contact force constraints as well as safety-critical precise foot placements on stepping stones, all while subject to model uncertainty. We conduct preliminary experimental validation of the proposed controller on a rectilinear spring-cart system under different types of model uncertainty and perturbations.
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ISSN:0018-9286
1558-2523
DOI:10.1109/TAC.2021.3059156